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A comparison of strategies for Markov chain Monte Carlo computation in quantitative genetics

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A comparison of strategies for Markov chain Monte Carlo computation in quantitative genetics

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dc.contributor.author Waagepetersen, R. es_ES
dc.contributor.author Ibáñez-Escriche, Noelia es_ES
dc.contributor.author Sorensen, D. es_ES
dc.date.accessioned 2020-01-16T21:01:49Z
dc.date.available 2020-01-16T21:01:49Z
dc.date.issued 2008 es_ES
dc.identifier.issn 0999-193X es_ES
dc.identifier.uri http://hdl.handle.net/10251/134686
dc.description.abstract [EN] In quantitative genetics, Markov chain Monte Carlo (MCMC) methods are indispensable for statistical inference in non-standard models like generalized linear models with genetic random effects or models with genetically structured variance heterogeneity. A particular challenge for MCMC applications in quantitative genetics is to obtain efficient updates of the high-dimensional vectors of genetic random effects and the associated covariance parameters. We discuss various strategies to approach this problem including reparameterization, Langevin-Hastings updates, and updates based on normal approximations. The methods are compared in applications to Bayesian inference for three data sets using a model with genetically structured variance heterogeneity. es_ES
dc.language Inglés es_ES
dc.publisher Springer (Biomed Central Ltd.) es_ES
dc.relation.ispartof Genetics Selection Evolution es_ES
dc.rights Reconocimiento (by) es_ES
dc.subject Langevin-Hastings es_ES
dc.subject Markov chain Monte Carlo es_ES
dc.subject Normal approximation es_ES
dc.subject Proposal distributions es_ES
dc.subject Reparameterization es_ES
dc.subject.classification PRODUCCION ANIMAL es_ES
dc.title A comparison of strategies for Markov chain Monte Carlo computation in quantitative genetics es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.1051/gse:2007042 es_ES
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Ciencia Animal - Departament de Ciència Animal es_ES
dc.description.bibliographicCitation Waagepetersen, R.; Ibáñez-Escriche, N.; Sorensen, D. (2008). A comparison of strategies for Markov chain Monte Carlo computation in quantitative genetics. Genetics Selection Evolution. 40(2):161-176. https://doi.org/10.1051/gse:2007042 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion https://doi.org/10.1051/gse:2007042 es_ES
dc.description.upvformatpinicio 161 es_ES
dc.description.upvformatpfin 176 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 40 es_ES
dc.description.issue 2 es_ES
dc.relation.pasarela 392553 es_ES


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